De Lausanne à Yaoundé : l’aventure des MOOCs
Bibliographic record
Abstract
La révolution digitale transforme les universités. Les cours massifs en ligne (MOOCs) ouverts, gratuits et produits par les meilleures universités en sont une expression majeure. Nous rendons compte ici d’un programme original de MOOCs déployés en Afrique et coproduits en partie par l’École polytechnique fédérale de Lausanne (EPFL) et des partenaires universitaires africains. En deux ans, 54 000 inscriptions nous sont parvenues de résidents d’Afrique, parmi lesquelles 17 000 ont réellement été actives, émanant pour les deux tiers de jeunes en formation, et pour un tiers d’adultes en formation continue. Au travers d’une meilleure acquisition de compétences par une plus large base d’apprenants, notre programme MOOCs pour l’Afrique - en collaboration avec les partenaires académiques du continent africain - vise à combler le manque de personnels qualifiés dans des domaines clés pour les économies émergentes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".